ABSTRACT: Lately, irrigated soybean production has increased; therefore, tools that can aid water resources management must be improved. Two experiments were carried out, the first one from May to August and the second one from September to December 2019. The experimental design included randomized blocks with five treatments and four replicates. In the control treatment (SE), irrigation was carried out to meet the crop’s water demand during all growth stages. In the other treatments, irrigation was interrupted at specific crop growth stages (TI = VC-V4, TII = V5-R1, TIII = R1-R5, and TIV = R5-R7), and then restored. After calibration, the model satisfactorily estimated the canopy cover, biomass, and soybean yield, with high values of determination coefficients (r² > 0.90), low RMSE and MBE values, and high values of EF. In experiment 1, the soil water content was overestimated in the SE, TI, and TIV treatments by 0.24%, 0.78%, and 0.23%, respectively, and underestimated by 3.3% and 5.5% in the TII and TIII treatments, respectively. In experiment 2, in the SE, TI, TII, TIII, and TIV treatments, the soil water content was underestimated by 6%, 3%, 4.6%, 5.9%, and 6.7%, respectively. Real evapotranspiration was overestimated in all treatments in both experiments, with low r² values in both experiments 1 (0.11- 0.23) and 2 (0.04 - 0.21). ABSTRACT Lately increased therefore improved 2019 replicates SE , (SE) crops s TI VCV4, VCV4 VCV VC V4, V4 V VC-V4 V5R1, V5R1 VR V5 R1, R1 R V5-R1 R1R5, R1R5 RR R5, R5 R1-R5 R5R7, R5R7 R7 R5-R7) restored calibration cover biomass yield r (r 0.90, 090 0.90 0 90 0.90) EF 024 24 0.24% 078 78 0.78% 023 23 0.23% respectively 33 3 3.3 55 5 5.5 6 6% 3% 46 4 4.6% 59 9 5.9% 67 7 6.7% 0.11 011 11 (0.11 0.23 0.04 004 04 (0.0 0.21. 021 0.21 . 21 0.21) 201 (SE VC-V V5R V5-R R1R R1-R R5R R5-R7 09 0.9 02 0.24 07 0.78 3. 5. 4.6 5.9 6.7 0.1 01 (0.1 0.2 0.0 00 (0. 20 R5-R 0. 0.7 4. 6. (0 (

RESUMO: Ultimamente, a produção de soja irrigada tem aumentado, portanto, ferramentas que auxiliem na gestão dos recursos hídricos devem ser aprimoradas. Foram realizados dois experimentos, o primeiro de maio a agosto e o segundo de setembro a dezembro de 2019. O delineamento experimental foi em blocos casualizados com cinco tratamentos e quatro repetições. No tratamento testemunha (SE), a irrigação foi realizada para atender a demanda hídrica da cultura durante todas as fases de crescimento. Nos demais tratamentos, a irrigação foi interrompida em determinados estádios de desenvolvimento da cultura (TI = VC-V4, TII = V5-R1, TIII = R1-R5 e TIV = R5-R7) e, a seguir, restabelecida. Após a calibração, o modelo estimou satisfatoriamente a cobertura do dossel, a biomassa e a produtividade da soja, com altos valores de coeficientes de determinação (r² > 0,90), baixos valores de RMSE e MBE e altos valores de EF. No experimento 1, o teor de água do solo foi superestimado nos tratamentos SE, TI e TIV em 0,24%, 0,78% e 0,23%, respectivamente, e subestimado em 3,3% e 5,5% nos tratamentos TII e TIII, respectivamente. No experimento 2, nos tratamentos SE, TI, TII, TIII e TIV, o teor de água no solo foi subestimado em 6%, 3%, 4,6%, 5,9% e 6,7%, respectivamente. A evapotranspiração real foi superestimada em todos os tratamentos em ambos os experimentos, com baixos valores de r² em ambos os experimentos 1 (0,11- 0,23) e 2 (0,04 - 0,21). RESUMO Ultimamente aumentado portanto aprimoradas 2019 repetições SE , (SE) crescimento VCV4, VCV4 VCV VC V4, V4 V VC-V4 V5R1, V5R1 VR V5 R1, R1 R V5-R1 R1R5 RR R5 R1-R R5R7 R7 R5-R7 seguir restabelecida calibração dossel r (r 0,90, 090 0,90 0 90 0,90) EF 024 24 0,24% 078 78 0,78 023 23 0,23% respectivamente 33 3 3,3 55 5 5,5 6 6% 3% 46 4 4,6% 59 9 5,9 67 7 6,7% 0,11 011 11 (0,11 0,23 0,04 004 04 (0,0 0,21. 021 0,21 . 21 0,21) 201 (SE VC-V V5R V5-R R1R R5R R5-R 09 0,9 02 0,24 07 0,7 3, 5, 4,6 6,7 0,1 01 (0,1 0,2 0,0 00 (0, 20 0, 4, 6, (0 (

ABSTRACT Brazil is the world’s largest soybean exporter. Over half of the cultivated area is in the Brazilian Savanna (Cerrado) region, where soybean is typically grown under rainfed conditions. However, soybeans have been cultivated in irrigated systems, further increasing water demand in the region, which already faces water problems. Therefore, it is crucial to generate technical information to support the management of water resources in irrigated soybean crops. This study aimed to estimate the water deficit sensitivity index of soybean crops. Two field experiments were carried out in randomized blocks with four treatments and four replicates from May to Aug 2019 and 2021. Three treatments with irrigation suspension were applied in three different phenological stages: vegetative, reproductive, and seed filling, and a fully irrigated control plot to meet the total plant demand. The results showed 40 % and 34 % reductions in soybean seed yield when water deficit was applied in stages R1-R5 and R5-R7, respectively, compared to the control treatment. There was a linear correlation with r2 values equal to 0.98, 0.97, and 0.99 for the relationships between seed yield and applied irrigation, seed yield and actual evapotranspiration (ETa), and ETa and irrigation, respectively. The yield response factors were equal to 0.12, 0.36, and 0.57 for the stages V2-R1, R1-R5, and R5-R7, respectively. The yield response factor for the soybean cycle was equal to 1.16. worlds world s exporter Cerrado (Cerrado region conditions However systems problems Therefore crops 201 2021 vegetative reproductive filling 4 3 R1R5 RR R1 R5 R R1-R R5R7, R5R7 R7, R7 R5-R7 respectively treatment r 098 0 98 0.98 097 97 0.97 099 99 0.9 ETa, , (ETa) 012 12 0.12 036 36 0.36 057 57 0.5 V2R1, V2R1 VR V2 R1, V V2-R1 R1R5, R5, 116 1 16 1.16 20 202 R1R R5R R5-R 09 9 0. (ETa 01 0.1 03 0.3 05 5 V2R V2-R 11 1.1 2 1.

ABSTRACT The Cerrado biome is a strategic region for Brazilian agriculture, and obtaining physical hydraulic properties is fundamental to understanding the dynamics of soil water and its impact on productivity. However, the lack and difficulty of obtaining such properties opens an opportunity to use pedotransfer functions (PTFs). In the context, the objective of the present study was to develop PTFs using multiple linear regression to estimate hydraulic conductivity of the saturated soil (Ks) and soil moisture at tensions of 0, 6, 10, 33, 100, and 1,500 kPa for the Cerrado biome. For this, two different predictor datasets were used. Dataset 1 consists of sand, silt, clay, bulk density, particle density, total porosity, microporosity, and macroporosity, and dataset 2 consists of the variables in dataset 1 plus soil moisture at field capacity (FC) and soil moisture at the permanent wilting point (PMP). Dataset 2 presented the best performance compared to Dataset 1 for estimating Ks and soil moisture, highlighting the importance of moisture in FC and PWP as predictors in the development of PTFs. However, the PTFs developed for Ks presented a low predictive capacity in all predictor datasets, unlike the soil moistures that presented high precision, with R² greater than 0.8 and errors close to zero. agriculture productivity However . (PTFs) context (Ks 0 6 10 33 100 1500 500 1,50 this used sand silt clay density porosity microporosity macroporosity (FC PMP. PMP (PMP) precision R 08 8 0. zero (PTFs 3 150 50 1,5 (PMP 15 5 1,

RESUMO O bioma Cerrado é uma estratégica região para a agricultura brasileira e a obtenção de propriedades físico-hídricas do solo é fundamental para a compreensão da dinâmica de água no solo e o seu impacto na produtividade. Contudo, a carência e a dificuldade de obter tais propriedades abre a oportunidade de uso de funções de pedotransferência (FPTs). Sendo assim, o objetivo do presente estudo foi desenvolver FPTs utilizando regressão linear múltipla para estimativa da condutividade hidráulica do solo saturado (Ks) e da umidade do solo nas tensões de 0, 6, 10, 33, 100 e 1.500 kPa para o bioma Cerrado. Para isto, dois diferentes conjuntos de dados preditores foram utilizados. O conjunto de dados 1 consiste de areia, silte, argila, densidade do solo, densidade de partículas, porosidade total, microporosidade e macroporosidade, e o conjunto de dados 2 que consiste das variáveis do conjunto 1 mais a umidade do solo na capacidade de campo (CC) e a umidade do solo no ponto de murcha permanente (PMP). O conjunto de dados 2 apresentou o melhor desempenho quando comparado ao conjunto de dados 1, tanto para a estimativa de Ks quanto para as umidades do solo, destacando a importância das umidades na CC e PMP como preditoras no desenvolvimento de FPTs. Contudo, as FPTs desenvolvidas para Ks apresentaram uma baixa capacidade preditiva em todos os conjuntos preditores, diferentemente das umidades que apresentaram alta precisão, com R² superiores a 0,8 e erros próximos de zero. físicohídricas físico hídricas produtividade Contudo . (FPTs) assim (Ks 0 6 10 33 1500 500 1.50 isto utilizados areia silte argila partículas total macroporosidade (CC PMP. (PMP) precisão R 08 8 zero (FPTs 3 150 50 1.5 (PMP 15 5 1.

RESUMO O bioma Cerrado tem apresentado desafios em conciliar sua expansão agrícola com a disponibilidade hídrica. Nesse sentido, o planejamento e o manejo de recursos hídricos são fundamentais para o desenvolvimento econômico, social e ambiental do bioma Cerrado, que tem sido prejudicado pela carência de dados, especialmente aqueles referentes às estratégias de irrigação, como, por exemplo, as curvas de retenção de água, essencial para compreender a dinâmica de água no solo. Contudo, como sua obtenção pode ser trabalhosa, seus parâmetros podem ser estimados indiretamente via Funções de Pedotransferência (FPTs). O objetivo do presente estudo foi desenvolver e avaliar FPTs para estimar parâmetros do modelo de van Genuchten, usado para descrever o processo de retenção de água, para o bioma Cerrado. Para o desenvolvimento das FPTs, foram usados os métodos de Regressão Linear Múltipla (RLM) e quatro algoritmos de aprendizado de máquina: Multivariate Adaptative Regression Splines (MARS), Random Forest (RF), Support Vector Regression (SVR) e K Nearest Neightbors (KNN). Dados de solo de duas localidades foram utilizados, sendo que as variáveis preditoras selecionadas em cada conjunto foram diferentes. As melhores estimativas foram obtidas para o parâmetro θs (umidade de saturação), com destaque para os modelos RF e SVR. Já para a θr (umidade residual), os modelos apresentaram uma capacidade preditiva moderada. Para os demais parâmetros, os modelos não apresentaram um desempenho satisfatório para α e n (parâmetros de ajuste).

ABSTRACT The Cerrado biome has presented challenges in reconciling its agricultural expansion with water availability. In this sense, water resources planning and management are fundamental for the economic, social, and environmental development of the Cerrado biome, which has been hampered by the lack of data, especially those referring to irrigation strategies, such as, for example, the water retention curve. The water retention curve is essential to understand water dynamics in the soil; however, obtaining it can be laborious, opening an opportunity for Pedotransfer Functions (PTFs). The current study aimed to develop and evaluate PTFs to estimate the fit parameters of the van Genuchten model for the Cerrado biome. Multiple Linear Regression (MLR) and four machine learning (ML) algorithms were used to develop the PTFs. The ML algorithms were the Multivariate Adaptive Regression Splines (MARS), Random Forest (RF), Support Vector Regression (SVR), and K Nearest Neighbors (KNN). Two combinations of soil data were evaluated, and the predictor variables used in each set were different. Using the RF and SVR models, the best estimates were obtained concerning the parameter θs (saturated water content). As for θr (residual water content), the models showed a moderate predictive capacity. For the other parameters, the models did not perform satisfactorily for α and n (fit parameters).

ABSTRACT Evapotranspiration (ET) is a key component of the hydrological cycle. Therefore, adequately estimating it is crucial to improving water resource planning and management.One of the most affordable methods of estimating ET is first to estimate reference crop evapotranspiration (ETo) and later associate it to crop and soil coefficients. The FAO Kc-ETo approach can be used only when ETo is computed with the FAO Penman-Monteith equation. However, low data availability may restict the equations used to estimate ETo. In this study, we assess and calibrate common methods used to estimate ETo under such conditions of limited data availability. Based on the annual calibration, the Makkink (NSE = 0.85) outperformed the Priestley-Taylor (NSE = 0.73), Hargreaves-Samani (NSE = 0.56), and Penman-Monteith temperature approach (NSE = 0.58). The seasonal calibration of parameters showed no significant improvement to the methods assessed (ΔNSE ≤ 0.01), except for the Priestley-Taylor (ΔNSE = 0.06). The performance of temperature-based equations was particularly limited due to the performance of the equation adopted to estimate global solar radiation. Thus, improving the representation of global solar radiation for limited data availability can also play a key role in improving ETo prediction.

RESUMO O aumento das disputas pelo uso de água no Cerrado brasileiro, tem demandado melhorias no manejo de irrigação e aumento da produtividade de uso da água. Neste contexto, a irrigação com déficit se apresenta como uma estratégia de manejo interessante, possibilitando economia de água sem prejuízos significativos à produtividade. O presente estudo teve como objetivo avaliar a fenologia e produtividade de uma cultivar de soja submetida a diferentes condições de déficit hídrico no solo. O delineamento experimental utilizado foi em blocos casualizados com cinco tratamentos e quatro repetições. Em cada tratamento, uma estratégia de irrigação foi aplicada com base na água disponível no solo (AD). O tratamento T1 foi realizado aplicando 80 a 100% AD; no tratamento T2, a variação permitida foi de 60 a 80% AD; no tratamento T3, foi de 40 a 60% AD; em T4, de 20 a 40% AD; e em T5, de 0 a 20% AD. Verificou-se que tanto no inverno quanto no verão, mesmo sem a necessidade de redução da retirada de água, é recomendável aplicar 60 a 80% da água disponível no solo para a cultura da soja, sem diminuir a produtividade. Em situações de restrição hídrica, é possível ter produtividade em torno de 55 e 70% no inverno e no verão, respectivamente, para a condição de 20 a 40% da água disponível no solo.

ABSTRACT The increase in disputes over water use in the Brazilian Cerrado has demanded improvements in irrigation management and increase in water use productivity. In this context, deficit irrigation is an interesting management strategy, as it enables water savings without significant losses of yield. The present study aimed to evaluate the phenology and yield of a soybean cultivar subjected to different soil moisture contents. The experimental design used was randomized blocks with five treatments and four replicates. In each treatment, an irrigation strategy was applied based on the available water in the soil (AW). The T1 treatment was performed by applying from 80 to 100% AW; in T2 treatment, the allowed variation was from 60 to 80% AW; in T3 treatment, it was from 40 to 60% AW; in T4, from 20 to 40% AW; and in T5, from 0 to 20% AW. It was verified that, in winter and summer, even without the need to reduce water withdrawal, it is recommended to apply from 60 to 80% of the available water in the soil for soybean crop, without decreasing yield. In situations of water restriction, it is possible to have yield of around 55 and 70% in winter and summer, respectively, for the condition from 20 to 40% of the available water in the soil.

RESUMO A cana-de açúcar é uma cultura de elevada demanda de água, sendo cultivo importante para o Nordeste do Brasil, região que apresenta limitação hídrica ao longo do ano para as plantas de cana. Assim, torna-se importante desenvolver estratégias para reduzir o volume de água de irrigação para a cultura. Objetivou-se no presente estudo determinar a data de plantio da cana-de-açúcar que coincida com a máxima disponibilidade de água proveniente da precipitação, durante seu ciclo de desenvolvimento. A precipitação efetiva foi estimada a partir do balanço de água do solo efetuado durante três ciclos de cultivo da cana-de açúcar, variedade RB 92579. A cultura foi conduzida sob irrigação por gotejamento subsuperficial, tendo sido plantada em cinco meses: Outubro, Novembro, Dezembro, Janeiro e Fevereiro, correspondentes à estação seca na região. O experimento foi conduzido na Usina Açúcar e Álcool Coruripe S.A., município de Coruripe, Estado de Alagoas, Brasil, durante os anos de 2012 a 2016. Para todas as datas de plantio e ciclos de crescimento avaliados, a precipitação média efetiva foi igual a 30% da precipitação total, na condição de cultivo sob irrigação, e de 54,5% quando não se considerou a irrigação como componente do balanço de água. Novembro foi o mês de plantio com a menor lâmina de irrigação aplicada no ciclo de cultivo da cana-de-açúcar, com economia potencial de água variando de 5 a 129 mm.

ABSTRACT Sugarcane is both an important crop for the Brazilian Northeast economy, which faces severe water scarcity, and a water-intensive crop. Thus, it is important to develop irrigation strategies to reduce irrigation water demand in the region. This study aims to determine the sugarcane planting date that results in the maximum rainwater availability to the crop in the growing cycle. The crop effective precipitation was estimated from a soil water balance performed during three planting cycles of sugarcane, cultivar ‘RB 92579’. The crop was planted under subsurface drip irrigation in five months: October, November, December, January, and February, corresponding to the dry season period of the region. The experiment was conducted at the Açúcar e Álcool Coruripe Mill, located in the Coruripe municipality, State of Alagoas, Brazil, during the years 2012 to 2016. For all planting dates and growing cycles studied, the average effective rainy precipitation was equal to 30% of the total rainfall under irrigated conditions and 54.5% without considering the irrigation component in the soil water balance. November was the planting date that resulted in the minimum irrigation depth for the sugarcane growing cycle, with the potential irrigation water saving ranging from 5 to 129 mm.

ABSTRACT Detecting trends in streamflow and rainfall series can have great significance for proper water resource management. Thus, the objective of this study was to analyze the trends of historical streamflow and rainfall series using nonparametric statistical tests. A historical series of pluviometric and fluviometric gauges, which belong to the hydrometeorological network of the Brazilian Water National Agency in the Santo Antônio River Basin, Brazil, from 1985 to 2014 were used. By applying statistical tests, it was found that the time series are independent and random, and from the total 24 rainfall gauges evaluated, 12 presented nonstationary behavior, exhibiting mostly decreasing trends. Based on the six fluviometric gauges used for the annual streamflow series, only the annual data of one gauge tended to decrease to the minimum streamflow. However, for the monthly series, three gauges showed decreasing trends between July and September. This decrease in streamflow may be a consequence of rainfall reductions, high water demand, and changes in land use and cover.

Abstract Optimization of water use for irrigation will only be possible with the adjustment of management, which is directly related to the correct estimate of the actual evapotranspiration of the crop. The present study aimed to evaluate different mathematical approaches used in estimating the actual evapotranspiration of a new soybean cultivar (BRS 7581RR) subjected to different water deficit conditions. For this, the ETa estimated by the FAO56 Dual, Jensen and Hermann, AquaCrop and Ritchie models was evaluated. The experimental design was randomized with five treatments and four replicates. Irrigation management in the treatments was conducted so as to maintain different levels of water available in the soil (AW). The T1 treatment was performed applying 80 to 100% AW; in T2 treatment, the allowed variation was 60 to 80% AW; in T3 treatment, it was 40 to 60% AW; in T4, from 20 to 40% AW; and in T5, from 0 to 20% AW. The results showed that the FAO56 Dual model showed better performance in soybean ETa estimation for winter conditions in most treatments, with NSE ranging from 0.42 to 0.83. In the summer, the Jensen and Hermann model showed the best results, with NSE ranging from 0.70 to 0.94.

RESUMO Em regiões onde a área irrigada é crescente e a disponibilidade hídrica é reduzida, como o Oeste do Estado da Bahia, Brasil, o emprego de técnicas que contribuam para melhorar a eficiência de uso de água é primordial. Uma das formas de melhor adequação da irrigação é através da melhoria do cálculo da evapotranspiração atual (ETa), que entre outros fatores, é influenciada pelo secamento do solo, sendo importante entender essa relação, que geralmente é contabilizada nos modelos de manejo de irrigação por meio do coeficiente de estresse hídrico (Ks). Este estudo objetivou estimar o coeficiente de estresse hídrico (Ks) por meio de informações obtidas via sensoriamento remoto, combinadas com informações de campo. Para isto, realizou-se um estudo no município de São Desidério, área localizada no Oeste da Bahia, utilizando imagens do satélite Landsat-8. O Ks foi calculado pela relação entre a evapotranspiração da cultura e a ETa, calculada pelo Simple Algorithm for Evapotranspiration Retrieving (SAFER). O Ks estimado por sensoriamento remoto apresentou para os estádios em desenvolvimento e médio, erros médios da ordem de 5,50%. No estádio final de desenvolvimento do milho os erros obtidos foram de 23,2%.

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

Resumo: O objetivo deste trabalho foi avaliar o desempenho do modelo “operational simplified surface energy balance” (SSEBop) na estimativa da evapotranspiração real (ETa) das culturas de soja e feijão irrigadas por pivô central. As estimativas do modelo foram obtidas de imagens digitais dos satélites Landsat 7 e Landsat 8 e comparadas à ETa obtida pelo método da razão de Bowen. O modelo foi avaliado pelo índice de concordância refinado (dr), pela raiz do erro médio quadrático (RMSE) e pelo erro médio absoluto (MBE). O desempenho do modelo nas estimativas da evapotranspiração real foi classificado pelo índice de desempenho (Pi). A relação entre as estimativas do modelo e o método da razão de Bowen apresentou correlação (r=0,94) e concordância (dr=0,82), com erro médio quadrático de 0,62 mm por dia e erro médio absoluto de 0,04 mm por dia. O desempenho das estimativas do modelo SSEBop, em comparação ao método da razão de Bowen, foi classificado como ótimo (Pi=0,77), o que comprova a utilidade do SSEBop e a precisão de suas estimativas de evapotranspiração real para culturas irrigadas como soja e feijão.

Abstract: The objective of this work was to evaluate the performance of the operational simplified surface energy balance (SSEBop) model in the estimation of the actual evapotranspiration (ETa) of soybean and bean crops irrigated by a central pivot. The model estimates were obtained from digital images of the Landsat 7 and Landsat 8 satellites, and were compared with the ETa obtained by the Bowen ratio method. The model was evaluated by the refined agreement index (dr), root mean square error (RMSE), and mean bias error (MBE). The model’s performance in the estimation of the ETa was classified by the performance index (Pi). The relationship between the estimates of the model and the Bowen ratio method showed correlation (r=0.94) and agreement (dr=0.82), with a mean square error of 0.62 mm per day and a mean bias error of 0.04 mm per day. The estimate perfomance of the SSEBop model in comparison with the Bowen ratio method, was classified as optimal (Pi=0.77), proving the SSEBop usability and precision to estimate ETa for irrigated crops, such as soybean and bean.

RESUMO. O objetivo deste trabalho foi apresentar uma nova metodologia para dimensionamento de RCAPs com base em modelagem probabilística. Para determinar uma demanda hídrica hipotética, utilizou-se a cultura do Eucalipto cultivada em casa de vegetação (CV). Dados meteorológicos foram utilizados para estimar, demanda (evapotranspiração) e oferta (precipitação incidente na cobertura da CV). A distribuição de probabilidade de Wakeby apresentou o melhor ajuste aos dados de precipitação; portanto, foi utilizada para modelar a curva de permanência do escoamento gerado na cobertura da CV e, assim, determinar o volume de um RCAP para suprir a demanda da cultura. Para um tempo de retorno (T) de 10 anos de excedente hídrico da demanda e de déficit hídrico da oferta, obteve-se um volume do RCAP de 13,60 m³. Assim, pela combinação de ocorrência simultânea dos eventos, pode-se concluir que a metodologia proposta permite dimensionar reservatórios com alta segurança de atendimento da demanda (T = 100 anos) e, consequentemente, com menor custo de implantação, comparado com as abordagens separadas (T = 10 anos).

ABSTRACT. The aim of this study was to propose a new methodology for reservoir rainwater dimensioning based on probabilistic modeling. Eucalyptus seedlings grown in a greenhouse were used to obtain a hypothetical water demand. Meteorological data were used to estimate the demand (evapotranspiration) and offer (rainfall over the greenhouse coverage). The probability distribution of Wakeby presented the best fit for the rainfall data; therefore, a Wakeby distribution was used to model the flow-duration curve of the greenhouse coverage. For a payback period (T) of 10 years of surplus water demand and water supply deficit, a reservoir with 13.60 m³ was obtained. The proposed methodology combined the simultaneous occurrence of the events to enable the scaling out of a reservoir with high safety to supply the required demand (T = 100 years) and therefore enables a lower cost of deployment compared to each approach separately (T = 10 years).

ABSTRACT This study aimed to compare methods for estimating reference evapotranspiration using an experimental basin in the Brazilian Cerrado, for water management purposes. For that, we estimated daily reference evapotranspiration over a certain period (time series between 1982 and 2012) through different empirical methods. These methods consisted of Blaney-Criddle (BC), Hargreaves & Samani (HS), ASCE Penman-Monteith (ASCE- PM), Penman (1948/1963) (PO), Priestley-Taylor (PT), which were all compared to the standard Penman-Monteith FAO-56 (PM-FAO56). Based on statistics, ASCE- PM, P and BC methods should be recommended for cerrado areas, either in rainy or dry seasons. After these, the PT also stood out. Among the less complex methods, based on temperature and energy data, PT method is recommended whether climatological data are scarce either in rainy or dry seasons. Yet, HS reached the greatest errors, a broad data spread and low estimate accuracy, but showing better performance in dry periods, thus remaining under restricted use.

ABSTRACT This study aimed to estimate the probability of climatological water deficit in an experimental watershed in the Cerrado biome, located in the central plateau of Brazil. For that, it was used a time series of 31 years (1982–2012). The probable climatological water deficit was calculated by the difference between rainfall and probable reference evapotranspiration, on a decennial scale. The reference evapotranspiration (ET0) was estimated by the standard FAO-56 Penman-Monteith method. To estimate water deficit, it was used gamma distribution, time series of rainfall and reference evapotranspiration. The adherence of the estimated probabilities to the observed data was verified by the Kolmogorov-Smirnov nonparametric test, with significance level (α-0.05), which presented a good adjustment to the distribution models. It was observed a climatological water deficit, in greater or lesser intensity, between the annual decennials 2 and 32.

A caracterização e a análise da distribuição espacial da pobreza podem ser úteis na aplicação de programas voltados para a redução de pobreza já que possibilitam a identificação de áreas onde a incidência é maior e cuja extensão muitas vezes ultrapassa as linhas territoriais oficiais. Nesse contexto, este artigo usa os mais recentes dados sobre pobreza rural municipal no Brasil para identificar os padrões espaciais de pobreza rural na Bacia do Rio São Francisco (BRSF). Indicadores de autocorrelação espacial I de Moran são gerados e usados para a construção de um mapa de clusters de pobreza rural. Os resultados indicam que a pobreza rural é espacialmente autocorrelacionada em algumas áreas da BRSF, nas quais municípios mais (menos) pobres tendem a se localizar perto de municípios mais (menos) pobres. Mais importante, talvez, os resultados sugerem a necessidade de se usar metodologias de análise que considerem explicitamente a localização como um fator explanatório da pobreza rural na bacia, como, por exemplo, econometria espacial.

This paper uses recently released município-level data on rural poverty in Brazil to identify and analyze spatial patterns of rural poverty in the São Francisco River Basin (SFRB). Moran's I statistics are generated and used to test for spatial autocorrelation, and to prepare cluster maps that locate rural poverty 'hot spots' and 'cold spots'. Our results indicate that poverty reduction policies in the SFRB should take into account the spatial distribution of poverty. Not only is poverty in the SFRB clustered spatially, but the bulk of the basin's poor resides in municípios that comprise the poverty 'hot spots' we identified. These clusters did not correspond to state-level boundaries (the political delineations often used to measure poverty and to manage poverty reduction programs), so scope may exist for geographically refocusing poverty reduction efforts to make them more efficient. Maybe more importantly the results set the stage for the use of spatial econometrics for a future multivariate analysis of rural poverty in the basin.